{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Creating a waterfall chart using Bokeh\n",
    "\n",
    "This is the notebook associated with the article at [Pbpython.com](http://pbpython.com/bokeh-bullet-waterfall.html)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bokeh.plotting import figure, show\n",
    "from bokeh.io import output_notebook\n",
    "from bokeh.models import ColumnDataSource, LabelSet\n",
    "from bokeh.models.formatters import NumeralTickFormatter\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <a href=\"https://bokeh.pydata.org\" target=\"_blank\" class=\"bk-logo bk-logo-small bk-logo-notebook\"></a>\n",
       "        <span id=\"c5208578-78c8-4c2a-aa52-f07b8d26c4e6\">Loading BokehJS ...</span>\n",
       "    </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "(function(root) {\n",
       "  function now() {\n",
       "    return new Date();\n",
       "  }\n",
       "\n",
       "  var force = true;\n",
       "\n",
       "  if (typeof (root._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "    root._bokeh_onload_callbacks = [];\n",
       "    root._bokeh_is_loading = undefined;\n",
       "  }\n",
       "\n",
       "  var JS_MIME_TYPE = 'application/javascript';\n",
       "  var HTML_MIME_TYPE = 'text/html';\n",
       "  var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n",
       "  var CLASS_NAME = 'output_bokeh rendered_html';\n",
       "\n",
       "  /**\n",
       "   * Render data to the DOM node\n",
       "   */\n",
       "  function render(props, node) {\n",
       "    var script = document.createElement(\"script\");\n",
       "    node.appendChild(script);\n",
       "  }\n",
       "\n",
       "  /**\n",
       "   * Handle when an output is cleared or removed\n",
       "   */\n",
       "  function handleClearOutput(event, handle) {\n",
       "    var cell = handle.cell;\n",
       "\n",
       "    var id = cell.output_area._bokeh_element_id;\n",
       "    var server_id = cell.output_area._bokeh_server_id;\n",
       "    // Clean up Bokeh references\n",
       "    if (id !== undefined) {\n",
       "      Bokeh.index[id].model.document.clear();\n",
       "      delete Bokeh.index[id];\n",
       "    }\n",
       "\n",
       "    if (server_id !== undefined) {\n",
       "      // Clean up Bokeh references\n",
       "      var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n",
       "      cell.notebook.kernel.execute(cmd, {\n",
       "        iopub: {\n",
       "          output: function(msg) {\n",
       "            var element_id = msg.content.text.trim();\n",
       "            Bokeh.index[element_id].model.document.clear();\n",
       "            delete Bokeh.index[element_id];\n",
       "          }\n",
       "        }\n",
       "      });\n",
       "      // Destroy server and session\n",
       "      var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n",
       "      cell.notebook.kernel.execute(cmd);\n",
       "    }\n",
       "  }\n",
       "\n",
       "  /**\n",
       "   * Handle when a new output is added\n",
       "   */\n",
       "  function handleAddOutput(event, handle) {\n",
       "    var output_area = handle.output_area;\n",
       "    var output = handle.output;\n",
       "\n",
       "    // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n",
       "    if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n",
       "      return\n",
       "    }\n",
       "\n",
       "    var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
       "\n",
       "    if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n",
       "      toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n",
       "      // store reference to embed id on output_area\n",
       "      output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
       "    }\n",
       "    if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
       "      var bk_div = document.createElement(\"div\");\n",
       "      bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
       "      var script_attrs = bk_div.children[0].attributes;\n",
       "      for (var i = 0; i < script_attrs.length; i++) {\n",
       "        toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
       "      }\n",
       "      // store reference to server id on output_area\n",
       "      output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
       "    }\n",
       "  }\n",
       "\n",
       "  function register_renderer(events, OutputArea) {\n",
       "\n",
       "    function append_mime(data, metadata, element) {\n",
       "      // create a DOM node to render to\n",
       "      var toinsert = this.create_output_subarea(\n",
       "        metadata,\n",
       "        CLASS_NAME,\n",
       "        EXEC_MIME_TYPE\n",
       "      );\n",
       "      this.keyboard_manager.register_events(toinsert);\n",
       "      // Render to node\n",
       "      var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
       "      render(props, toinsert[toinsert.length - 1]);\n",
       "      element.append(toinsert);\n",
       "      return toinsert\n",
       "    }\n",
       "\n",
       "    /* Handle when an output is cleared or removed */\n",
       "    events.on('clear_output.CodeCell', handleClearOutput);\n",
       "    events.on('delete.Cell', handleClearOutput);\n",
       "\n",
       "    /* Handle when a new output is added */\n",
       "    events.on('output_added.OutputArea', handleAddOutput);\n",
       "\n",
       "    /**\n",
       "     * Register the mime type and append_mime function with output_area\n",
       "     */\n",
       "    OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
       "      /* Is output safe? */\n",
       "      safe: true,\n",
       "      /* Index of renderer in `output_area.display_order` */\n",
       "      index: 0\n",
       "    });\n",
       "  }\n",
       "\n",
       "  // register the mime type if in Jupyter Notebook environment and previously unregistered\n",
       "  if (root.Jupyter !== undefined) {\n",
       "    var events = require('base/js/events');\n",
       "    var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
       "\n",
       "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
       "      register_renderer(events, OutputArea);\n",
       "    }\n",
       "  }\n",
       "\n",
       "  \n",
       "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "    root._bokeh_timeout = Date.now() + 5000;\n",
       "    root._bokeh_failed_load = false;\n",
       "  }\n",
       "\n",
       "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "     \"<div style='background-color: #fdd'>\\n\"+\n",
       "     \"<p>\\n\"+\n",
       "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "     \"</p>\\n\"+\n",
       "     \"<ul>\\n\"+\n",
       "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "     \"</ul>\\n\"+\n",
       "     \"<code>\\n\"+\n",
       "     \"from bokeh.resources import INLINE\\n\"+\n",
       "     \"output_notebook(resources=INLINE)\\n\"+\n",
       "     \"</code>\\n\"+\n",
       "     \"</div>\"}};\n",
       "\n",
       "  function display_loaded() {\n",
       "    var el = document.getElementById(\"c5208578-78c8-4c2a-aa52-f07b8d26c4e6\");\n",
       "    if (el != null) {\n",
       "      el.textContent = \"BokehJS is loading...\";\n",
       "    }\n",
       "    if (root.Bokeh !== undefined) {\n",
       "      if (el != null) {\n",
       "        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n",
       "      }\n",
       "    } else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(display_loaded, 100)\n",
       "    }\n",
       "  }\n",
       "\n",
       "\n",
       "  function run_callbacks() {\n",
       "    try {\n",
       "      root._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "    }\n",
       "    finally {\n",
       "      delete root._bokeh_onload_callbacks\n",
       "    }\n",
       "    console.info(\"Bokeh: all callbacks have finished\");\n",
       "  }\n",
       "\n",
       "  function load_libs(js_urls, callback) {\n",
       "    root._bokeh_onload_callbacks.push(callback);\n",
       "    if (root._bokeh_is_loading > 0) {\n",
       "      console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "      return null;\n",
       "    }\n",
       "    if (js_urls == null || js_urls.length === 0) {\n",
       "      run_callbacks();\n",
       "      return null;\n",
       "    }\n",
       "    console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "    root._bokeh_is_loading = js_urls.length;\n",
       "    for (var i = 0; i < js_urls.length; i++) {\n",
       "      var url = js_urls[i];\n",
       "      var s = document.createElement('script');\n",
       "      s.src = url;\n",
       "      s.async = false;\n",
       "      s.onreadystatechange = s.onload = function() {\n",
       "        root._bokeh_is_loading--;\n",
       "        if (root._bokeh_is_loading === 0) {\n",
       "          console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "          run_callbacks()\n",
       "        }\n",
       "      };\n",
       "      s.onerror = function() {\n",
       "        console.warn(\"failed to load library \" + url);\n",
       "      };\n",
       "      console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "    }\n",
       "  };var element = document.getElementById(\"c5208578-78c8-4c2a-aa52-f07b8d26c4e6\");\n",
       "  if (element == null) {\n",
       "    console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'c5208578-78c8-4c2a-aa52-f07b8d26c4e6' but no matching script tag was found. \")\n",
       "    return false;\n",
       "  }\n",
       "\n",
       "  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.15.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.15.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.15.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-0.12.15.min.js\"];\n",
       "\n",
       "  var inline_js = [\n",
       "    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "    \n",
       "    function(Bokeh) {\n",
       "      \n",
       "    },\n",
       "    function(Bokeh) {\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.15.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.15.min.css\");\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.15.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.15.min.css\");\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.15.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.15.min.css\");\n",
       "    }\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
       "    \n",
       "    if ((root.Bokeh !== undefined) || (force === true)) {\n",
       "      for (var i = 0; i < inline_js.length; i++) {\n",
       "        inline_js[i].call(root, root.Bokeh);\n",
       "      }if (force === true) {\n",
       "        display_loaded();\n",
       "      }} else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(run_inline_js, 100);\n",
       "    } else if (!root._bokeh_failed_load) {\n",
       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "      root._bokeh_failed_load = true;\n",
       "    } else if (force !== true) {\n",
       "      var cell = $(document.getElementById(\"c5208578-78c8-4c2a-aa52-f07b8d26c4e6\")).parents('.cell').data().cell;\n",
       "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "    }\n",
       "\n",
       "  }\n",
       "\n",
       "  if (root._bokeh_is_loading === 0) {\n",
       "    console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "    run_inline_js();\n",
       "  } else {\n",
       "    load_libs(js_urls, function() {\n",
       "      console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "      run_inline_js();\n",
       "    });\n",
       "  }\n",
       "}(window));"
      ],
      "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n\n  if (typeof (root._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n    root._bokeh_onload_callbacks = [];\n    root._bokeh_is_loading = undefined;\n  }\n\n  \n\n  \n  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  var NB_LOAD_WARNING = {'data': {'text/html':\n     \"<div style='background-color: #fdd'>\\n\"+\n     \"<p>\\n\"+\n     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n     \"</p>\\n\"+\n     \"<ul>\\n\"+\n     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n     \"</ul>\\n\"+\n     \"<code>\\n\"+\n     \"from bokeh.resources import INLINE\\n\"+\n     \"output_notebook(resources=INLINE)\\n\"+\n     \"</code>\\n\"+\n     \"</div>\"}};\n\n  function display_loaded() {\n    var el = document.getElementById(\"c5208578-78c8-4c2a-aa52-f07b8d26c4e6\");\n    if (el != null) {\n      el.textContent = \"BokehJS is loading...\";\n    }\n    if (root.Bokeh !== undefined) {\n      if (el != null) {\n        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(display_loaded, 100)\n    }\n  }\n\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n    }\n    finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.info(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(js_urls, callback) {\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls == null || js_urls.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = js_urls.length;\n    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      var s = document.createElement('script');\n      s.src = url;\n      s.async = false;\n      s.onreadystatechange = s.onload = function() {\n        root._bokeh_is_loading--;\n        if (root._bokeh_is_loading === 0) {\n          console.log(\"Bokeh: all BokehJS libraries loaded\");\n          run_callbacks()\n        }\n      };\n      s.onerror = function() {\n        console.warn(\"failed to load library \" + url);\n      };\n      console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.getElementsByTagName(\"head\")[0].appendChild(s);\n    }\n  };var element = document.getElementById(\"c5208578-78c8-4c2a-aa52-f07b8d26c4e6\");\n  if (element == null) {\n    console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'c5208578-78c8-4c2a-aa52-f07b8d26c4e6' but no matching script tag was found. \")\n    return false;\n  }\n\n  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.15.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.15.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.15.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-0.12.15.min.js\"];\n\n  var inline_js = [\n    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\n    \n    function(Bokeh) {\n      \n    },\n    function(Bokeh) {\n      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.15.min.css\");\n      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.15.min.css\");\n      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.15.min.css\");\n      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.15.min.css\");\n      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.15.min.css\");\n      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.15.min.css\");\n    }\n  ];\n\n  function run_inline_js() {\n    \n    if ((root.Bokeh !== undefined) || (force === true)) {\n      for (var i = 0; i < inline_js.length; i++) {\n        inline_js[i].call(root, root.Bokeh);\n      }if (force === true) {\n        display_loaded();\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    } else if (force !== true) {\n      var cell = $(document.getElementById(\"c5208578-78c8-4c2a-aa52-f07b8d26c4e6\")).parents('.cell').data().cell;\n      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n    }\n\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(js_urls, function() {\n      console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "output_notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create the initial dataframe\n",
    "index = ['sales','returns','credit fees','rebates','late charges','shipping']\n",
    "data = {'amount': [350000,-30000,-7500,-25000,95000,-7000]}\n",
    "df = pd.DataFrame(data=data,index=index)\n",
    "\n",
    "# Determine the total net value by adding the start and all additional transactions\n",
    "net = df['amount'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>amount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>sales</th>\n",
       "      <td>350000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>returns</th>\n",
       "      <td>-30000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>credit fees</th>\n",
       "      <td>-7500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rebates</th>\n",
       "      <td>-25000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>late charges</th>\n",
       "      <td>95000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>shipping</th>\n",
       "      <td>-7000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              amount\n",
       "sales         350000\n",
       "returns       -30000\n",
       "credit fees    -7500\n",
       "rebates       -25000\n",
       "late charges   95000\n",
       "shipping       -7000"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create additional columns that we will use to build the waterfall\n",
    "df['running_total'] = df['amount'].cumsum()\n",
    "df['y_start'] = df['running_total'] - df['amount']\n",
    "\n",
    "# Where do we want to place the label\n",
    "df['label_pos'] = df['running_total']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>amount</th>\n",
       "      <th>running_total</th>\n",
       "      <th>y_start</th>\n",
       "      <th>label_pos</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>sales</th>\n",
       "      <td>350000</td>\n",
       "      <td>350000</td>\n",
       "      <td>0</td>\n",
       "      <td>350000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>returns</th>\n",
       "      <td>-30000</td>\n",
       "      <td>320000</td>\n",
       "      <td>350000</td>\n",
       "      <td>320000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>credit fees</th>\n",
       "      <td>-7500</td>\n",
       "      <td>312500</td>\n",
       "      <td>320000</td>\n",
       "      <td>312500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rebates</th>\n",
       "      <td>-25000</td>\n",
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       "      <td>312500</td>\n",
       "      <td>287500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>late charges</th>\n",
       "      <td>95000</td>\n",
       "      <td>382500</td>\n",
       "      <td>287500</td>\n",
       "      <td>382500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>shipping</th>\n",
       "      <td>-7000</td>\n",
       "      <td>375500</td>\n",
       "      <td>382500</td>\n",
       "      <td>375500</td>\n",
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       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              amount  running_total  y_start  label_pos\n",
       "sales         350000         350000        0     350000\n",
       "returns       -30000         320000   350000     320000\n",
       "credit fees    -7500         312500   320000     312500\n",
       "rebates       -25000         287500   312500     287500\n",
       "late charges   95000         382500   287500     382500\n",
       "shipping       -7000         375500   382500     375500"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# We need to have a net column at the end with the totals and a full bar\n",
    "df_net = pd.DataFrame.from_records([(net, net, 0, net)], \n",
    "                                   columns=['amount', 'running_total', 'y_start', 'label_pos'],\n",
    "                                   index=[\"net\"])\n",
    "df = df.append(df_net)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>amount</th>\n",
       "      <th>running_total</th>\n",
       "      <th>y_start</th>\n",
       "      <th>label_pos</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>sales</th>\n",
       "      <td>350000</td>\n",
       "      <td>350000</td>\n",
       "      <td>0</td>\n",
       "      <td>350000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>returns</th>\n",
       "      <td>-30000</td>\n",
       "      <td>320000</td>\n",
       "      <td>350000</td>\n",
       "      <td>320000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>credit fees</th>\n",
       "      <td>-7500</td>\n",
       "      <td>312500</td>\n",
       "      <td>320000</td>\n",
       "      <td>312500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rebates</th>\n",
       "      <td>-25000</td>\n",
       "      <td>287500</td>\n",
       "      <td>312500</td>\n",
       "      <td>287500</td>\n",
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       "    <tr>\n",
       "      <th>late charges</th>\n",
       "      <td>95000</td>\n",
       "      <td>382500</td>\n",
       "      <td>287500</td>\n",
       "      <td>382500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>shipping</th>\n",
       "      <td>-7000</td>\n",
       "      <td>375500</td>\n",
       "      <td>382500</td>\n",
       "      <td>375500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>net</th>\n",
       "      <td>375500</td>\n",
       "      <td>375500</td>\n",
       "      <td>0</td>\n",
       "      <td>375500</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              amount  running_total  y_start  label_pos\n",
       "sales         350000         350000        0     350000\n",
       "returns       -30000         320000   350000     320000\n",
       "credit fees    -7500         312500   320000     312500\n",
       "rebates       -25000         287500   312500     287500\n",
       "late charges   95000         382500   287500     382500\n",
       "shipping       -7000         375500   382500     375500\n",
       "net           375500         375500        0     375500"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# We want to color the positive values gray and the negative red\n",
    "df['color'] = 'grey'\n",
    "df.loc[df.amount < 0, 'color'] = 'red'\n",
    "\n",
    "# The 10000 factor is used to make the text positioned correctly.\n",
    "# You will need to modify if the values are significantly different\n",
    "df.loc[df.amount < 0, 'label_pos'] = df.label_pos - 10000\n",
    "df[\"bar_label\"] = df[\"amount\"].map('{:,.0f}'.format)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <tbody>\n",
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       "      <th>sales</th>\n",
       "      <td>350000</td>\n",
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       "      <td>350000</td>\n",
       "      <td>grey</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>returns</th>\n",
       "      <td>-30000</td>\n",
       "      <td>320000</td>\n",
       "      <td>350000</td>\n",
       "      <td>310000</td>\n",
       "      <td>red</td>\n",
       "      <td>-30,000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>credit fees</th>\n",
       "      <td>-7500</td>\n",
       "      <td>312500</td>\n",
       "      <td>320000</td>\n",
       "      <td>302500</td>\n",
       "      <td>red</td>\n",
       "      <td>-7,500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rebates</th>\n",
       "      <td>-25000</td>\n",
       "      <td>287500</td>\n",
       "      <td>312500</td>\n",
       "      <td>277500</td>\n",
       "      <td>red</td>\n",
       "      <td>-25,000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>late charges</th>\n",
       "      <td>95000</td>\n",
       "      <td>382500</td>\n",
       "      <td>287500</td>\n",
       "      <td>382500</td>\n",
       "      <td>grey</td>\n",
       "      <td>95,000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>shipping</th>\n",
       "      <td>-7000</td>\n",
       "      <td>375500</td>\n",
       "      <td>382500</td>\n",
       "      <td>365500</td>\n",
       "      <td>red</td>\n",
       "      <td>-7,000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>net</th>\n",
       "      <td>375500</td>\n",
       "      <td>375500</td>\n",
       "      <td>0</td>\n",
       "      <td>375500</td>\n",
       "      <td>grey</td>\n",
       "      <td>375,500</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              amount  running_total  y_start  label_pos color bar_label\n",
       "sales         350000         350000        0     350000  grey   350,000\n",
       "returns       -30000         320000   350000     310000   red   -30,000\n",
       "credit fees    -7500         312500   320000     302500   red    -7,500\n",
       "rebates       -25000         287500   312500     277500   red   -25,000\n",
       "late charges   95000         382500   287500     382500  grey    95,000\n",
       "shipping       -7000         375500   382500     365500   red    -7,000\n",
       "net           375500         375500        0     375500  grey   375,500"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Build the Bokeh figure\n",
    "\n",
    "# Limit the tools to only these three\n",
    "TOOLS = \"box_zoom,reset,save\"\n",
    "\n",
    "# Build the source data off the df dataframe\n",
    "source = ColumnDataSource(df)\n",
    "\n",
    "# Create the figure and assign range values that look good for the data set\n",
    "p = figure(tools=TOOLS, x_range=list(df.index), y_range=(0, net+40000), plot_width=800, title = \"Sales Waterfall\")\n",
    "p.grid.grid_line_alpha=0.3\n",
    "\n",
    "# Add the segments\n",
    "p.segment(x0='index', y0='y_start', x1=\"index\", y1='running_total', source=source, color=\"color\", line_width=55)\n",
    "\n",
    "# Format the y-axis as dollars\n",
    "p.yaxis[0].formatter = NumeralTickFormatter(format=\"($ 0 a)\")\n",
    "p.xaxis.axis_label = \"Transactions\"\n",
    "\n",
    "# Add the labels\n",
    "labels = LabelSet(x='index', y='label_pos', text='bar_label', text_font_size=\"8pt\", level='glyph',\n",
    "         x_offset=-20, y_offset=0, source=source)\n",
    "p.add_layout(labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
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       "\n",
       "<div class=\"bk-root\">\n",
       "    <div class=\"bk-plotdiv\" id=\"5f102e27-9bf3-43e2-9297-f719355d68b2\"></div>\n",
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       "  var render_items = [{\"docid\":\"0af0f5de-039b-4fad-afdb-3c10bea62d85\",\"elementid\":\"5f102e27-9bf3-43e2-9297-f719355d68b2\",\"modelid\":\"eec691b0-6b6a-45ff-8365-f8d008272cdf\"}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        embed_document(root);\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "      attempts++;\n",
       "      if (attempts > 100) {\n",
       "        console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\")\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
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